Monte Carlo simulations of optical human sinusitis diagnostics

Monte Carlo simulations of optical human sinusitis diagnostics
Lisa Simonsson,
Department of Physics, Lund Institute of Technology, P.O. Box 118, SE-221 00 Lund, Sweden
April 2, 2007
1 Introduction
Sinusitis is an inflammation of the paranasal
sinus mucosa, which is treated with antibiotics
and often followed by one week of sick-leave.
Every year, more than 37 million people in
the US are diagnosed with sinusitis. Today,
the diagnosis of sinusitis is mostly based on
the anamnestic history of the patient, and in
some cases on paraclinical investigations such
as X-ray, ultrasound, and low-dose computerized
tomography. Unfortunately, unnecessary
antibiotic treatment is very common due to the
difficult diagnoses. Therefore, there is a great
need for simple, non-intrusive alternatives or
complementary methods to detect sinusitis [1,
2].
We describe computer simulations related to
a new spectroscopic method for human sinusitis
detection, which was demonstrated by L.
Persson et al. [3]. This method is based on
the sharp spectroscopic absorptive imprint of
molecular oxygen characterizing an air filled
cavity traversed by diffusive light. Narrowband
diode laser radiation is launched through
the facial skeleton and traversing the frontal
sinus cavities in the forehead or the maxillary
sinuses in the cheekbone (see Fig. 1 for sinuses
location). The light is then diffusely scattered
in the deeper lying tissues with part of the light
again traversing the cavities and again scattered
in the facial tissue to reach an external
detector. For the maxillary sinuses, an alter-
Frontal sinus
Maxillary sinus
Figure 1: MRI image indicating the location of
human maxillary and frontal sinuses. A light
path illustrating the present technique is also
included.
native light transmission geometry can be employed,
where the laser light is injected into the
bucal mucosa, and detected externally.
In Ref. [3] we successfully demonstrated sinus
cavity monitoring on a healthy human volunteer.
The study was supported by extensive
experimental trials on tissue-like plastic phantom
materials separated by an air gap in order
to simulate the human anatomy. A so-called
equivalent mean path length, L eq , is estimated,
which corresponds to how far the light must
travel in ambient air to obtain the same absorption
signal as in the sample, by using a
method called standard addition [4].
We have now performed detailed simulations
of light propagation to verify the experimental
data and to further guide the develop-
cm
1

a
Secondary
Scatterer
1 Primary S
l 1
Air gap
S 1
l 1
Scatterer
Mask
Prism
Light
S 2
l 2
Plexiglas
Filter
S 2
Detector
l 2
b
Light
Mask
Filter
Detector
Primary
Scatterer
Air gap
Secondary
Scatterer
Figure 2: Phantom models used in experiments
and simulations representing (a) Measurements
on the human frontal sinuses with
a backscattering detection geometry. (b) Measurements
on the human maxillary sinuses with
a transmission detection geometry.
ment of the current technique. For this study
we used the Advanced Systems Analysis Program
(ASAP TM ) software which operates on
the Monte Carlo concept.
2 Results
In Fig.3 and 4 the result from the comparison
with the experimental data is seen. The influence
of different optical properties is seen in
Fig. 5 A study of different detection apertures
is seen in Fig. 6.
3 Conclusion
The power of Monte Carlo simulations in
understanding and optimizing the experimental
conditions for human sinus monitoring is
demonstrated. The possibility of working with
arbitrary geometries in the ASAP TM approach
is particularly valuable. The simulations agree
well with experimental data for the limited
setup conditions studied so far. The influence
of different optical properties is also shown to
a
L eq
[mm]
b
L eq
[mm]
20
15
10
5
Fixed primary
scatterer thickness
0
0 20 40 60
Air distance [mm]
20
15
10
5
Fixed secondary
scatterer thickness
l
2
> 30 mm
l
2
= 10 mm
l
2
= 3 mm
l
1
= 3 mm
l
1
= 10 mm
0
0 20 40 60
Air distance [mm]
Exp.
Sim.
Exp.
Sim.
Exp.
Sim.
Exp.
Sim.
Exp.
Sim.
Figure 3: Phantom experiments and simulations
for the backscattering model, representing
measurements on the human frontal sinuses.
be significant. The simulations show that the
outer radius should be as large as possible.
They also show that an inner radius as large as
possible should be used with an upper limit set
by the experimental signal-to-noise ratio. This
gives us confidence in using the simulations
presented in the process of developing a new
and clinically relevant modality for human
sinus diagnostics.
References
[1] Health Matters, Sinusitis, Nat. Inst. of
Allergy and Infectious Diseases, US Dept. of
Health and Human Services, Bethesda (2005).
[2] P. Stierna, G. Karlsson, I. Melén, and
M. Jannert, “Aspect on Sinusitis - Diagnosis
and threatment in adults,” Proceedings from
meeting of the Swedish Association of Otorhinolaryngol,
HNS, Stockholm (1995).
2

a
L eq
[mm]
b
L eq
[mm]
60 Fixed primary
scatterer thickness
40
20
0
0 10 20 30 40
Air distance [mm]
60
40
20
Fixed secondary
scatterer thickness
l
2
= 10 mm
l
2
= 6 mm
l
1
= 10 mm
l
1
= 6 mm
0
0 10 20 30 40
Air distance [mm]
Exp.
Sim.
Exp.
Sim.
Exp.
Sim.
Exp.
Sim.
L eq
[mm]
4
3
2
1
0
Delrin
Adult in vitro
Adult in vivo
Neonate in vivo
10 20 30 40 50 60 70
Air distance [mm]
Figure 5: Different optical properties of the
primary and secondary scatterer were used in
simulations of the backscattering geometry.
Figure 4: Phantom experiments and simulations
for the transmission detection model, representing
measurements on the human maxillary
sinuses.
[3] L. Persson, K. Svanberg, and S. Svanberg,
“On the potential of human sinus
cavity diagnostics using diode laser gas spectroscopy,”
Appl. Phys. B 82, 313–317 (2006).
[4] S. Svanberg, Atomic and Molecular
Spectroscopy, 4th edition, Chapter 8,
Springer-Verlag, Berlin Heidelberg (2004)
[5] L. Persson, E. Kristensson, L. Simonsson
and S. Svanberg, “Monte Carlo Simulations of
optical human sinusitis diagnostics,” Journal
of Biomedical Optics Submitted (2006).
a
L eq
[mm]
b
L eq
[mm]
12
10
8
6
4
2
Constant inner radius
0 r o = 5 mm
0 10 20 30 40 50 60 70
Air distance [mm]
12
10
8
6
4
2
r = 10 mm
o
r = 9 mm i
r = 4 mm i
Constant outer radius
0
0 10 20 30 40 50 60 70
Air distance [mm]
Figure 6: Simulations for different annular detection
apertures in the case of backscattering
detection geometry. (a) The inner radius of the
annular detection aperture, r i , is kept constant
while the outer radius, r o , is varied. (b) The
outer radius of the annular detection aperture,
r o , is kept constant while the inner radius, r i ,
is varied.
3